Discover Elasticsearch’s architecture and capabilities. Learn about indexing and storing data, conducting precise queries, including fuzzy searches, and executing real-time data analysis effectively.

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This course explores Elasticsearch, an open-source, Java-based, full-text search and analytics engine that harnesses the power of the Lucene library. You’ll discover its capabilities as a versatile search engine for business data, offering the ability to store information, conduct searches on accurate and typo-ridden text, and perform real-time data analysis on vast datasets.

Throughout this course, you will gain comprehensive insights into the architecture of Elasticsearch and master the art of indexing and storing data within the Elasticsearch framework. You will progress to learn how to execute various types of queries, including fuzzy queries, and explore the intricacies of each operation and how it is implemented within Elasticsearch.

After completing the course, you’ll have gained a comprehensive understanding of the internal mechanisms of Elasticsearch and developed the skills to effectively use it for your data management and analysis requirements.

Elasticsearch Fundamentals: Indexing and Querying Data

# Challenge

In this challenge, you will be working with a dataset of product information stored in Elasticsearch. The dataset contains various attributes for each product, such as `name`, `description`, `price`, `category`, `brand`, `color`, `availability`, `rating`, and `seller`. Your task is to perform different search queries on Elasticsearch to gain insights and retrieve specific products based on given criteria.





The `products` index comprises several fields with their respective data types and purposes as follows:

- `name`: This field stores the name of the product. It allows full-text search capabilities, enabling users to efficiently search for products based on their names.

- `description`: This field holds the description of the product. It contains detailed information about the product.

- `price`: This field stores the numeric value of the product's price. It is represented as a floating-point number, allowing for precise calculations and range-based searches, such as finding products within a specific price range.

- `category`: This field represents the category of the product. It is stored as a `keyword`, enabling exact match searches. Users can search for products in a particular category or filter products based on specific categories.

- `brand`: This field contains the brand or manufacturer of the product. It is also stored as a `keyword`.

- `color`: This field stores the color of the product. It is stored as a `keyword`.
- `availability`: This field indicates the availability status of the product. It is stored as a `keyword`.

- `rating`: This field represents the rating of the product. It is stored as a floating-point number.

- `seller`: This field contains the name or identifier of the product's seller. It is stored as a `keyword`, enabling exact match searches. 


Test your query writing skills in Elasticsearch.


Introduction to Elasticsearch

Getting started on Elasticsearch

Text Analysis

Search on ElasticSearch

Aggregation

Conclusion

Integrate Elasticsearch in the Ruby on Rails Application

Challenge: Search on Elasticsearch

Challenge